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UNIVERSITI PUTRA MALAYSIA
REPRODUCTIVE ALLOMETRY AND PLASTICITY IN RELATION TO PLANT POPULATION DENSITY IN SOYBEAN [(Glycine max L.) Merrill.]
HASSAN HAMAD HASSAN EL-ZEADANI
FP 2015 70
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REPRODUCTIVE ALLOMETRY AND PLASTICITY IN RELATION TO
PLANT POPULATION DENSITY IN SOYBEAN [(Glycine max L.) Merrill.]
By
HASSAN HAMAD HASSAN EL-ZEADANI
Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,
in Fulfilment of the Requirements for the Degree of Doctor of Philosophy
March 2015
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DEDICATION
TO WHOM IN WHICH THEIR TRUE LOVE AND SUPPORT WERE BEHIND
MY SUCCESS
TO MY MOTHER AND TO THE MEMORY OF MY FATHER
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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment
of the requirement for the degree of Doctor of Philosophy
REPRODUCTIVE ALLOMETRY AND PLASTICITY IN RELATION TO
PLANT POPULATION DENSITY IN SOYBEAN [(Glycine max L.) Merrill.]
By
HASSAN HAMAD HASSAN EL-ZEADANI
March 2015
ABSTRACT
Chairperson: Associate Professor Adam Puteh, PhD
Faculty: Agriculture
The vegetative and reproductive stages during plant growth are strongly
interdependent and ultimately influence the potential yield. The biomass produced
by plant during the early part of its life cycle are eventually allocated to various
vegetative and reproductive structures and functional plant processes. From an
agronomic perspective, biomass quantification to different plant organs especially to
the economic yield based on allometric and plasticity analyses are limited. Thus, the
general objective of this study was to evaluate the use of allometry and plasticity
approaches in comparing several soybean varieties in relation to changes in plant
population densities especially under the tropical growing environment. The specific
objectives were: (i) to determine the effect of plant population density of selected
vegetable- and grain-type varieties of soybean on changes of growth rates and seed
fill duration at specific reproductive growth stages and the relationships of individual
seed growth rate (SGRi) and seed filling period (SFP) with yield components, (ii)
toquantify allometric changes based on relative growth rate of leaf and seed mass,
and source-sink relationship due to plant population pressures at specific
reproductive growth stages, and (iii) to determine yield plasticity responses to plant
density variations based on individual plant and per area basis, and the use of
plasticity for designing the optimal field planting density. In the first experiment
(2010), three soybean varieties [AGS 190 (vegetable-type), Palmetto and Deing
(grain-types)] were grown at 20, 30, and 40 plants m-2. The second experiment
(2011), AGS190 and grain-types of Argomolio and Willis were grown at 20, 30, and
50 plants m-2. At 20, 30, and 40 or 50plants m-2 are considered as low (L), normal
(N), and high planting density (H), respectively. The field experimental design in
both years was randomized complete block design (RCBD) with three replications.
Plant density did not affect the SGRi or SFP, but they differ among varieties during
different reproductive growth stages. Dry matter accumulation in the seed was
highest during reproductive growth stages from full size seed to physiological
maturity stage (R6 to R7, respectively). This period of seed growth and development
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had the highest SGRi and SFP. Increased plant density had decreased seed number
of individual plant. Seed number per plant adjustments indicated the stability of
individual final seed size within variety that was insensitive to the changes in plant
density. Both SGRi and SFP were correlated negatively with seed number per plant
and positively with final seed size. In this study (under humid tropical growing
conditions) the selected vegetable- and grain-type soybeans could be grown
successfully even with maximum daily temperature ˃ 32˚C, and the seed number,
seed weight per plant, and number of plants per area were important features to
determine yield potential.
The source-sink relationship of leaf and seed mass per plant with the consideration of
time were analyzed allometrically by taking the ratio of respective relative growth
rate of leaves (RGRl) to seeds (RGRs) with a model of 𝛼 =RGR𝑙
RGR𝑠 , where α =
allometry. The derived ‘α’ values explain three types of biomass allocation to seeds.
At α > 0 allometry zone, the leaves daily current photoassimilate was used for further
leaf growth while partitioning some for seed development. When at α = 0 zone, it
was a point in which all current photoassimilate in green leaves was partitioned to
seed development, and it corresponds to the beginning of linear phase of seed
growth. It occurred at the beginning of R6 for vegetable-type of AGS190 and the
beginning of R5 for the grain-types of Deing, Palmetto, Argomolio, and Willis. In
the zone of α < 0, the leaves begin to senesce and the increase in seed size that
primarily due to mobilization current and stored assimilates from vegetative organs
and also current photosynthetic produced by the green tissues of reproductive organ.
Related to allometry analysis, the beginning of the effective seed filling period
(ESFP) was determined based on the intersection point of the proportionate leaf RGR
and seed mass to their respective predicted maximum values that produced by the
curves of 𝑅𝐺𝑅 = 𝑏 + 2𝑐𝑡 𝑎𝑛𝑑 𝑦 = 𝑒(𝑎+bt+𝑐𝑡2), respectively. The resultant was
∫(𝑏 + 2𝑐𝑡)٭𝑑𝑡 − ∫(𝑒𝑎+bt+𝑐𝑡2𝑑𝑡٭( = 0, where ‘*’ indicates the predicted values of
the leaf RGR and seed mass that firstly converted to their proportionate values based
on their maximum predicted values, and t is days after planting. The ESFP that
generated in this study is an alternative to effective filling period (EFP) method with
an additional feature that simultaneously includes vegetative and reproductive
growth consideration. The method of ESFP was found quantitatively and
physiologically reliable in the five tested soybean varieties for two growing seasons.
Average overall densities, the ESFP and EFP for all varieties studied were shorter or
similar to the duration of morphological stages of beginning seed (R5) to
physiological maturity (R7).
Plasticity based on per plant and per area basis were indexed as pt and Pt,
respectively. Varieties tested showed high plasticity (pt) in seed number per plant
for density setting of L-H than that of L-N where L, N, and H were the low, normal,
and high densities, respectively. This result indicated that seed number per plant was
gradually reduced with increasing plant density. Genetically, the range of plasticity
was slightly less for the large seeded vegetable-type variety (AGS190) than those of
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the small seeded grain-type varieties (Argomolio, Palmetto, Willis and Deing) grown
in Malaysia tropical conditions. The plasticity of seed number based on per area
basis (Pt) was predicted by new model 𝑃𝑡 = −[(1 + bn + 2𝑐𝑛2)𝑒(𝑎+bn+𝑐𝑛2)]. There were three types of plasticity in seed m-2 across plant densities pressure;
positive, negative and no phenotypic plasticities. The curve that started with a
positive plasticity with increasing plant density had optimum planting density related
design at its lower density (20 plants m-2) which was observed in AGS190 and
Willis. A trend that started with a negative plasticity with increasing density, the
optimal planting density occurred when Pt = 0. At this plasticity, the estimated
optimum planting densities for Deing, Palmetto, and Argomolio ranged between22 -
29 plants m-2 to achieve maximum seed number m-2. The optimum yield per area
occurred at low to normal density range. Per area plasticity is more practical than the
per plant basis plasticity when describing the maximum yield for the designing of
planting densities in soybean cultivation in tropical environments.
The study had successfully used the allometry and plasticity in describing the
agronomic and physiological indicators in growing soybean under the tropical
condition. The physiologists, breeders and agronomists should exploit on the
allometry of RGR of leaves over seeds (α = 0), per plant plasticity (pt= 0), and per
area plasticity (Pt = 0 or the first appearing of Pt when Pt start with positive value in
Pt versus density curve), respectively in developing and expending soybean varieties
that could be successfully grown under humid tropical environments.
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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia
sebagai memenuhi keperluan untuk ijazah Doktor Falsafah
REPRODUKTIF ALLOMETRI DAN PLASTISITI BERHUBUNG DENGAN
KEPADATAN POPULASI TUMBUHAN DALAM KACANG SOYA
[(Glycine max L.) Merrill.]
Oleh
HASSAN HAMAD HASSAN EL-ZEADANI
Mac 2015
ABSTRAK
Pengerusi: Profesor Madya Adam Puteh, PhD
Fakulti: Pertanian
Peringkat vegetative dan pembiakan semasa pertumbuhan tumbuhan adalah saling
bergantung yang akhirnya mempengaruhi potensi hasil. Tumbuhan menghasilkan
biomass semasa permulaan kitaran hayatnya, yang akhirnya biomas tersebut
diperuntukkan kepada pelbagai struktur vegetatif dan pembiakan dan fungsi proses
tumbuhan. Dari perspektif agronomi, kuantifikasi biomass kepada organ-organ
tumbuhan yang berbeza terutama kepada hasil ekonomi berdasarkan analisis
allometri dan plastisiti adalah terhad. Oleh itu, objektif umum kajian ini adalah
untuk menentukan penggunaan pendekatan "allometri dan keplastikan" dalam
menilai beberapa varieti kacang soya dalam persekitaran tropika. Objektif khusus
adalah, (i) untuk menentukan kesan kepadatan populasi tumbuhan pada kadar
perubahan dan tempoh tumbesaran di peringkat tumbesaranbiji benih, dan hubungan
kadar pertumbuhan benih (SGRi) dan tempoh pengisian benih (SFP) keatas
komponen hasil dan hasil, (ii) untuk menilai pendekatan fisiologi kuantitatif dalam
perubahan allometri berdasarkan kadar pertumbuhan relatif antaradaun dan berat biji
sepokok serta hubungan sumber-sinkidan tekanan populasi tumbuhan pada peringkat
reproduktif, dan (iii) untuk menentukan variasi keplastikan hasil pada kepadatan
tanaman berdasarkan response sepokok dan per unit kawasan, dan penggunaan
keplastikan untuk rekabentuk kepadatan penanaman yang optimum. Dalam kajian
pertama (2010), tiga varieti kacang soya [AGS 190 (jenissayuran), Palmetto dan
Deing (jenisbijirin)] ditanam pada 20, 30, dan 40 pokok m-2.. Eksperimen kedua
(2011) menggunakan AGS190 dan jenisbijirin Argomolio dan Willis yang ditanam
pada 20, 30, 50 pokok m-2. Reka bentuk eksperimen dilapangan dalam kedua-dua
tahun ialah rekabentuk blok lengkap terawak (RCBD) dengan tiga replikasi.
Kepadatan tanaman tidak menjejaskan SGRi atau SFP, tetapi ia berbeza antara
varietisemasa peringkat pertumbuhan pembiakan yang berlainan. Pengumpulan
bahan kering di dalam benih adalah paling tinggi semasa peringkat pertumbuhan
pembiakan masing-masing dari R6 ke peringkat R7. Ini tempoh pertumbuhan biji
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dan mempunyai SGRi dan SFP tertinggi. Peningkatan kepadatan tanaman telah
menurunkan bilangan benih sepokok. Pelarasan bilangan biji per pokok
menunjukkan kestabilan saiz individu biji untuk setiap varieti yang tidak peka
kepada perubahan kepadatan tanaman. Kedua-dua SGR dan SFP telah berkorelasi
negatif dengan bilangan biji bagi setiap tumbuhan dan positif dengan saiz benih
akhir. Dalam kajian ini di bawah keadaan lembap pertumbuhan tropika, tanaman
pilihan dan jenis bijirin kacang soya boleh ditanam berjaya walaupun dengan suhu
maksimum harian ˃ 32 ˚C, dan jumlah biji, berat biji sepokok, dan jumlah biji per
kawasan adalah ciri-ciri penting untuk menentukan potensi hasil.
Hubungan sumber-sinki daun dan berat biji per pokok dengan masa dianalisis secara
allometri dengan mengambil nisbah kadar pertumbuhan relatif diantara daun (RGRl)
dan benih (RGRs) dengan model 𝛼 =RGR𝑙
RGR𝑠 , di mana α = allometri. Nilai 'α'
menerangkan tiga jenis peruntukan biojisim untuk perkembangan biji. Pada α > 0
zon allometri ini, hasil fotoasimilasi daun harian semasa adalah digunakan untuk
penerusan pertumbuhan daun manakala pembahagian beberapa untuk perkembangan
biji. Pada α = 0 zon adalah titik di mana semua fotoasimilasi semasa dalam daun
hijau dibahagikan untuk perkembanganbiji, dan ia sepadan dengan permulaan fasa
linear pertumbuhan biji. Ia berlaku pada awal R6 untuk AGS190 dan pada awal R5
untuk jenis-bijirin Deing, Palmetto, Argomolio dan Willis. Pada zon α < 0, daun
mula senesce dan peningkatan saiz biji adalah terutamanya disebabkan oleh
mobilisasi semasa dan tersimpan daripada organ-organ vegetatif dan juga fotosintesis
terkiniyang dihasilkan daripada tisu hijau organ pembiakan (buah).
Berdasarkan daripada analisis allometri, permulaan tempoh pengisian biji efektif
(ESFP) dapat ditentukan berdasarkan titik persilangan keluk RGR daun berkadar dan
jisim biji yang disesuaikan dari pada data diramalkan oleh 𝑅𝐺𝑅 = 𝑏 +
2𝑐𝑡 𝑑𝑎𝑛 𝑦 = 𝑒(𝑎+bt+𝑐𝑡2), masing-masing. Ini telah menghasilkan ∫(𝑏 +
2𝑐𝑡)٭𝑑𝑡 − ∫(𝑒𝑎+bt+𝑐𝑡2𝑑𝑡٭( = 0, di mana '*' menunjukkan nilai-nilai yang
diramalkan daripada RGR daun dan jisim biji yang kemudiannya ditukar kepada
nilai-nilai yang diseragamkan berdasarkan nilai-nilai maksimum yang diramalkan.
Kaedah ESFP yang dihasilkan dalam kajian ini adalah alternatif untuk kaedah EFP
dengan taktor tambahan yang pada masa yang sama termasuk vegetatif dan
pertumbuhan reproduktif.Kaedah ESFP ditemukan secara kuantitatif dan fisiologi
yang sesuai dalam lima varieti kacang soya yang diuji selama dua musim. ESFP dan
EFP untuk semua varieti yang diteliti adalah lebih pendek atau sama dengan tempoh
fasa morfologi R5 ke R7.
Plastisiti berdasarkan kepada basis sepokok dan seunit kawasan adalah masing-
masing, diindeks sebagai pt dan Pt. Varieti yang diuji menunjukkan plastisitas tinggi
(pt) dalam jumlah biji sepokok untuk pengaturan kepadatan L-H daripada L-N di
mana L, N, dan H adalah masing-masing, pada kepadatan tendah, normal, dan tinggi.
Ini menunjukkan bahwa jumlah biji sepokok secara bertahap telah dikurangi dengan
peningkatan kepadatan tanaman. Secara genetik, julat keplastikan adalah sedikit
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rendah untuk soya jenis sayuran berbiji besar (AGS190) dibandingkan variti jenis
bijiran yang berbiji kecil (Argomolio, Palmetto, Willis dan Deing). Plastisiti jumlah
biji berdasarkan seunit kawasan dapat dikira berdasarkan 𝑃𝑡 = −[(1 + bn +
2𝑐𝑛2)𝑒(𝑎+bn+𝑐𝑛2)]. Terdapat tiga jenis Plastisiti bilangan dalam biji m-2 di pelbagai
kepadatan tanaman ; positif, negatif dan tidak plastisiti fenotip.Keluk yang bermula
dengan keplastikan positif dan dengan peningkatan kepadatan tanaman mempunyai
rekabentuk yang berkait dengan kepadatan penanaman optimum ia itu pada
kepadatan rendah (20 pokok m-2), seperti yang di tunjukan oleh AGS190 dan Willis.
Trend yang bermula dengan plastisiti negatif dan dengan meningkatkan kepadatan,
kepadatan tanaman optimum berlaku apabila Pt = 0 Pada plastisiti ini, anggaran jarak
tanaman optimum untuk Deing, Palmetto, dan Argomolio adalah antara 22-29 pokok
m-2 untuk mendapatkan bilangan biji per m-2 yang maksimum. Hasil optimum
diperoleh pada julat kepadatan rendah ke normal. Plastisiti berdasarkan unit
kawasan adalah lebih praktikal dibandingkan dengan hasil per pokok adalam mereka
bentuk jarak tanaman dalam penanaman kacang soya di persekitaran tropika.
Kajian ini telah berjaya menggunakan allometri dan plastisiti dalam menggunakan
petunjuk agronomi dan fisiologi dalam penanama kacang soya di environmen
tropika. Fisiologis, pembiak baka, danagronomis perlu mengeksploitasi allometri
daun daripada biji (α = 0) dan keplastikan per pokok (pt= 0) dan keplastikan per
kawasan (Pt = 0) masing-masing dalam pembangunan dan perkembangan varieti
kacang soya yang boleh ditanam dengan berjayg di persekitaran tropika lembap.
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ACKNOWLEDGEMENTS
In the Name of Allah, Most Gracious, Most Merciful, all praise and thanks are due to
Allah, and peace and blessings be upon his Messenger. The author would like to
sincerely express his deep gratitude and appreciation to his supervisory committee
chairman Associate Professor Dr. Adam Puteh (Head, Department of Crop Science),
for his guidance, suggestions, and encouragement throughout the author’s graduate
studies.
The author would like to express the most sincere appreciation to Dr. Ahmad B.
Selamat (Co-supervisor) for his unfailing advice in making this thesis a reality.
Deepest thanks and sincere appreciation also go to the members of my supervisory
committee, Associate Professor Dr. Zainal Abidin Bin Mior Ahmad and Associate
Professor Dr. Muftah M. Shalgam for their constructive contributions and
suggestions. Thanks are to Mr. Shafar Jefri and to the staff members of UPM,
Malaysia for their direct or indirect involvements with this research.
The author acknowledges the financial support and permission from the Libyan
Ministry of Higher Education which made his studies and research in Malaysia
possible, and he also acknowledges the Libyan Ambassador, Counsellor Student
Affairs, and Embassy staff in Kuala Lumpur and his sincere to Libyan friends who
are studying in Malaysia for their kind attention and support.
Thanks are sincerely and deeply to his sisters, brothers, relatives, friends, and to
Mr. Salah Ali Zidan for their love, motivation, and support.
Last but not least, the author would like to express his deepest appreciation to his
mother (Om-assaad), wife (Omalaz), daughters (Maha and Muna), and sons
(Mohamed and Mohanned) for their moral support, great patience, love, and
understanding.
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This thesis submitted to the Senate of Universiti Putra Malaysia and has been
accepted as fulfilment of the requirement for the degree of Doctor of Philosophy.
The members of the Supervisory Committee were as follows:
Adam Puteh, PhD
Associate Professor
Faculty of Agriculture
Universiti Putra Malaysia
(Chairman)
Ahmad B. Selamat, PhD
Associate Professor
Faculty of Agriculture
Universiti Putra Malaysia
(Member)
Zainal Abidin Bin Mior Ahmad, PhD
Associate Professor
Faculty of Agriculture
Universiti Putra Malaysia
(Member)
Muftah M. Shalgam,PhD
Associate Professor
Faculty of Agriculture
Sebha University, Libya
(Member)
BUJANG KIM HUAT, PhD
Professor and Dean
School of Graduate Studies
Universiti Putra Malaysia
Date:
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Declaration by graduate student
DECLARATION
I hereby conform that:
This thesis is my original work;
Quotations, illustration and citation have been dully referenced;
This thesis has not been submitted previously or concurrently for other degree
at any other institutions;
Intellectual properly from thesis and copyright of thesis are fully owned by
Universiti Putra Malaysia, as according to the University Putra Malaysia
(Research) Rules 2012;
Written permission must be obtain from supervisor and the office of Deputy
Vice-Chancellor (Research and Innovation) before thesis is published (in the
form of written, printed or electronic from) including books, journals,
modules, proceeding, popular writings, seminar papers, manuscripts, posters,
reports, lecture notes, learning modules or any other materials as stated in the
Universiti Putra Malaysia (Research) Rules 2012;
There is no plagiarism or data falsification/fabrication in the thesis, and
scholarly integrity is upheld as according to the Universiti Putra Malaysia
(Research) Rules 2012. The thesis has undergone plagiarism detection
software.
Signature: Date:
Name and Matric No.: Hassan Hamad Hassan El-Zeadani, GS24060
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TABLE OF CONTENTS
Page
ABSTRACT i
ABSTRAK iv
ACKNOWLEDGEMENTS vii
APPROVAL viii
DECLARATION x
LIST OF TABLES xv
LIST OF FIGURES xviii
LIST OF APPENDICES xx
LIST OF ABBREVIATIONS xxii
CHAPTER 1 1
1 GENERAL INTRODUCTION 1
2 LITERATURE REVIEW 5
2.1 Origin of Soybean 5
2.2 Physiological and Agronomic Characteristics of Soybeans 5
2.3 Soybean Growth and Development 6
2.3.1 Vegetative and Reproductive Stages 6
2.3.2 Seed Formation and Development 8
2.4 Soybean Growing Requirement 10
2.5 Soybean Yield Potential 11
2.6 Plant Population Density and Seed Yield 12
2.7 Soybean Growth Dynamics 13
2.8 Seed Growth Rate and Filling Period 14
2.9 Reproductive Allometry in Relation to Plant Density 15
2.9.1 Reproductive Allocation Patterns 15
2.9.2 Allometric Basis Consideration 16
2.9.3 Vegetative and Reproductive Allometric Relationships 17
2.10 Phenotypic Plasticity in Plants 18
3 SOYBEAN GROWTH DYNAMICS, SEED FILLING PERIOD,
AND YIELD RESPONSES TO PLANT DENSITY AT SPECIFIC
REPRODUCTIVE GROWTH STAGES 20
3.1 Introduction 20
3.2 Materials and Methods 22
3.2.1 Experiment Sites and Design 22
3.2.2 Crop Management Practices 24
3.2.3 Plant Sampling and Analysis 24
3.2.4 Mathematical Modeling in Computing Growth Rate as a
Function of Time 25
3.3 Statistical Analysis 26
3.4 Results 26
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3.4.1 Soybean Growth Dynamics during Specific Reproductive
Stages 26
3.4.2 Correlation of Seed Growth Rate (SGR) with Leaf Growth
Rate (LGR) and Plant Growth Rate (PGR) Based on per Plant
Basis 34
3.4.3 Seed Growth Rate Based on Individual Seed Dry Weight
Basis 37
3.4.4 Seed Filling Period and Maturity 37
3.4.5 Seed Yield and Yield Components 42
3.4.6 Correlations between SGRi, SFP and Yield and Yield
Components 42
3.5 Discussion 45
3.6 Conclusion 48
4 ALLOMETRIC CHANGES IN RESPONSE TO CHANGES IN
PLANTING DENSITY 49
4.1 Introduction 49
4.2 Materials and Methods 50
4.2.1 Theoretical Mathematical Considerations 50
4.2.1.1 Relative Growth Rate 50
4.2.1.2 Allometry 51
4.2.1.3 Estimation of the Beginning of the Effective
Seed Filling Period (ESFP) Based on Functions
for Allometrical Analysis 52
4.3 Statistical Analysis 53
4.4 Results 53
4.4.1 Seed and Leaf RGR Dynamics during Specific
Reproductive Stages 53
4.4.2 Allometric of Leaf to Seed Mass 53
4.4.3 The Effective Seed Filling Period (ESFP) Estimation
Related to Allometrical Approaches 60
4.5 Discussion 62
4.6 Conclusions 69
5 VARIATION IN PHENOTYPIC PLASTICITY OF SEED
NUMBER IN RELATION TO PLANT DENSITY 70
5.1 Introduction 70
5.2 Materials and Methods 71
5.2.1 Plant Component Computation 71
5.2.2 Theoretical and Mathematical Consideration of
Plasticity 71
5.3 Statistical analysis 73
5.4 Results 73
5.4.1 Influence of Soybean Varieties and Plant Density
Changes on Vegetative Mass and Seed Number. 73
5.4.2 Relationships between Vegetative Mass and Seed
Number 78
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5.4.3 Phenotypic Plasticity (pt) at Different Reproductive
Growth Stages on Per Plant Basis. 78
5.4.4 Phenotypic Plasticity (Pt) of Seed Number over Plant
Density Pressures on Per Area Basis. 81
5.5 Discussion 83
5.6 Conclusions 84
6 SUMMARY, CONCLUSION AND RECOMMENDATIONS FOR
FUTURE RESEARCH 86
6.1 Summary and Conclusion 86
6.2 Recommendations for Future Research 90
REFERENCES 92
APPENDICES 107
BIODATA OF STUDENT 120
LIST OF PUBLICTIONS 121
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LIST OF TABLES
Table
Page
2.1 Description of soybean vegetative growth stages (VE-Vn) 8
2.2 Description of soybean reproductive growth stages (R1-R8)
9
2.3 Number of days between soybean reproductive stages
9
3.1 Constants (a, b and c), R2, F value, p ≥ F of seed, leaf and plant dry
weight (y) versus day after planting (DAP = t) with the function of
ln(𝑦) = 𝑎 + bt + 𝑐𝑡2 or [𝑦 = 𝑒(𝑎+bt+𝑐𝑡2)] in 2010 experiment. N =
15 for each density.
30
3.2 Constants (a, b and c), R2, F value, p ≥ F of seed, leaf and plant dry
weight (y) versus day after planting (DAP = t) with the function of
ln(𝑦) = 𝑎 + bt + 𝑐𝑡2 or [𝑦 = 𝑒(𝑎+bt+𝑐𝑡2)] in 2011 experiment. N =
15 for each density.
31
3.3 The effects of planting density and soybean varieties on individual
seed growth rate (SGRi) at specific reproductive growth stages in
2010 experiment
38
3.4 The effects of planting density and soybean varieties on individual
seed growth rate (SGRi) at specific reproductive growth stages in
2011 experiment
39
3.5 The effects of planting density and soybean varieties on seed filling
period (SFP) at specific reproductive growth stages in 2010
experiment
40
3.6 The effects of planting density and soybean varieties on seed filling
period (SFP) at specific reproductive growth stages in 2011
experiment
41
3.7 The effects of planting density and soybean varieties on yield and
yield components in 2010 experiment
43
3.8 The effects of planting density and soybean varieties on yield and
yield components in 2011 experiment
44
3.9 Correlation of seed filling period (SFP) and individual seed growth
rate (SGRi) versus seed number per plant, final seed size, and yield
over all varieties and planting densities in 2010 experiment
45
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3.10 Correlation of seed filling period (SFP) and individual seed growth
rate (SGRi) versus seed number per plant, final seed size, and yield
over all varieties and planting densities in 2011 experiment
45
4.1 Predicted relative growth rate (RGR) of seed mass at the beginning
of each specific reproductive growth stages of the soybean varieties
at three planting densities with the function of 𝑅𝐺𝑅 = 𝑏 + 2𝑐𝑡 in
2010 and 2011 experiments
57
4.2 Predicted relative growth rate (RGR) of leaf mass at the beginning of
each specific reproductive growth stages of the soybean varieties at
three planting densities with the function of 𝑅𝐺𝑅 = 𝑏 + 2𝑐𝑡 in 2010
and 2011 experiments
58
4.3 The allometry coefficient (α) of leaf RGR versus seed RGR on per
plant basis at specific reproductive growth stages of the soybean
varieties at three planting densities in 2010 and 2011 experiments
59
4.4 The effects of planting density and soybean varieties on predicted of
the beginning of the effective seed filling period in 2010 experiment
65
4.5 The effects of planting density and soybean varieties on predicted of
the beginning of the effective seed filling period in 2011 experiment
66
5.1 Variation in seed number per plant due to different planting densities
of soybean varieties at specific reproductive growth stages in 2010
experiment
74
5.2 Variation in seed number per plant due to different planting densities
of soybean varieties at specific reproductive growth stages in 2011
experiment
75
5.3 Variation in vegetative mass (g plant-1) due to different planting
densities of soybean varieties at specific reproductive growth stages
in 2010 experiment
76
5.4 Variation in vegetative mass (g plant-1) due to different planting
densities of soybean varieties at specific reproductive growth stages
in the 2011 experiment
77
5.5 Correlations of seed number versus vegetative mass per plant of
soybeans over all planting densities in 2010 experiment
78
5.6 Correlations of seed number versus vegetative mass per plant of
soybeans over all planting densities in 2011 experiment
78
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5.7 Constants (a, b and c), R2, F value, p of seeds m-2 (Y) with the non-
linear regression of Y = 𝑛𝑒(𝑎+𝑏𝑛+𝑐𝑛2) , where n is planting
density, N = 9 for each soybean variety in 2010 and 2011
experiments
82
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LIST OF FIGURES
Figure Page
2.1 Figure 2.1: Reproductive soybean development stages. Source;
Pedersen (2004), and Hoffman (2004).
7
3.1 Aerial photograph of the Universiti Putra Malaysia (UPM),
Serdang Selangor, Malaysia in indicating the locations of the two
sites of the respective field studies. Source: Google maps 2014.
23
3.2 Soybean varieties grown at UPM (Faculty of Agriculture, field 2)
in 2010 with experimental design RCBD
23
3.3 The leaf mass (y) versus days after planting (t): (𝑦 = 𝑒(𝑎+bt+𝑐𝑡2))
at different planting densities of soybean varieties at both
experiments conducted in 2010 and 2011.
27
3.4 The Seed mass (y) versus days after planting (t): (𝑦 =
𝑒(𝑎+bt+𝑐𝑡2)) at different planting densities of soybean varieties at
both experiments conducted in 2010 and 2011.
28
3.5 The Total plant mass (y) versus days after planting (t): (𝑦 =
𝑒(𝑎+bt+𝑐𝑡2)) at different planting densities of soybean varieties at both
experiments conducted in 2010 and 2011.
29
3.6 The leaf growth rate per plant (y) versus days after planting (t):
(𝑦 = (𝑏 + 2𝑐𝑡)𝑒(𝑎+bt+𝑐𝑡2)) at different planting densities of soybean
varieties at both experiments conducted in 2010 and 2011
32
3.7 The Seed growth rate per plant (y) versus days after planting (t):
(𝑦 = (𝑏 + 2𝑐𝑡)𝑒(𝑎+bt+𝑐𝑡2)) at different planting densities of soybean
varieties at both experiments conducted in 2010 and 2011
33
3.8 The plant growth rate per plant (y) versus days after planting (t):
(𝑦 = (𝑏 + 2𝑐𝑡)𝑒(𝑎+bt+𝑐𝑡2)) at different planting densities of soybean
varieties at both experiments conducted in 2010 and 2011
34
3.9 The relationship between seed and leaf growth rate on per plant basis of
soybean at different planting densities in both experiments conducted in
2010 and 2011
35
3.10 The relationship between seed and plant growth rate on per plant basis
of soybean at different planting densities in both experiments conducted
in 2010 and 2011
36
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4.1 The seed RGR versus days after planting (𝑅𝐺𝑅 = 𝑏 + 2𝑐𝑡) at
different planting densities of soybean varieties in both
experiments conducted in 2010 and 2011
55
4.2 The leaf RGR versus days after planting (𝑅𝐺𝑅 = 𝑏 + 2𝑐𝑡) at
different planting densities of soybean varieties in both
experiments conducted in 2010 and 2011
56
4.3 The instantaneous allometric scaling exponent (α) of leaf- to seed-
RGR at different planting densities of soybean varieties with the
function of α = RGRl / RGRs , where l and s superscript refers to
leaf and seed mass per plant, respectively at both experiments
conducted in 2010 and 2011
60
4.4 Intersection point and area between curves of soybean leaf RGR
and seed mass based on Eq. (4.11), the maximum predicted values
of leaf RGR and seed mass over the reproductive period of R3-
R6.5 were used in converting into the proportionate predicted
values in 2010 experiment
63
4.5 Intersection point and area between curves of soybean leaf RGR
and seed mass based on Eq. (4.11), the maximum predicted values
of leaf RGR and seed mass over the reproductive period of R3-
R6.5 were used in converting into the proportionate predicted
values in 2011 experiment
64
5.1 The effects of planting density on phenotypic plasticity of seed
plant-1 at different growth stages (R3 to R6) of soybean varieties
79
5.2 The effects of planting density on phenotypic plasticity of
vegetative mass plant-1 at different growth stages (R3 to R6) of
soybean varieties
80
5.3 Variation in yield (Y) and its plasticity (Pt) of soybean varieties
as predicted by Y = 𝑛𝑒(𝑎+𝑏𝑛+𝑐𝑛2) and 𝑃𝑡 = −[(1 + 𝑏𝑛 +
2𝑐𝑛2)𝑒(𝑎+𝑏𝑛+𝑐𝑛2)], where n is planting density pressures in both
experiments 2010 and 2011
82
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LIST OF APPENDICES
Appendix
Page
A-1 Source, origin and Soybean varieties studied
107
A-2 Meteorological data for growing season; May to August 2010
107
A-3 Meteorological data for growing season; June to September 2011
107
B-1 The effects of planting density and soybean varieties on leaf dry
weight (g plant-1) at specific reproductive growth stages in 2010
experiment
108
B-2 The effects of planting density and soybean varieties on leaf dry
weight (g plant-1) at specific reproductive growth stages in 2011
experiment
109
B-3 The effects of planting density and soybean varieties on seed dry
weight (g plant-1) at specific reproductive growth stages in 2010
experiment
110
B-4 The effects of planting density and soybean varieties on seed dry
weight (g plant-1) at specific reproductive growth stages in 2011
experiment
111
B-5 The effects of planting density and soybean varieties on plant dry
weight (g plant-1) at specific reproductive growth stages in 2010
experiment
112
B-6 The effects of planting density and soybean varieties on plant dry
weight (g plant-1) at specific reproductive growth stages in 2011
experiment
113
C-1 The seed mass (y) per plant versus days (t) after planting (𝑦 =
𝑒(𝑎+bt+𝑐𝑡2)) and leaf RGR versus days after planting ( 𝑅𝐺𝑅 =𝑏 + 2𝑐𝑡) at different planting densities of soybean varieties of
the experiment that conducted in 2010
114
C-2 The seed mass (y) per plant versus days (t) after planting (𝑦 =
𝑒(𝑎+bt+𝑐𝑡2)) and leaf RGR versus days after planting ( 𝑅𝐺𝑅 =𝑏 + 2𝑐𝑡) at different planting densities of soybean varieties of
the experiment that conducted in 2011
115
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D-1 Predicted of seeds m-2 (Y) as affected by planting density and
soybean varieties in the form of the non-linear regression of
Y = 𝑛𝑒(𝑎+𝑏𝑛+𝑐𝑛2) , where n is planting density and a, b, and c
are constants as indicated in Table 5.7 in 2010 experiment
116
D-2 Predicted of seeds m-2 (Y) as affected by planting density and
soybean varieties in the form of the non-linear regression of
Y = 𝑛𝑒(𝑎+𝑏𝑛+𝑐𝑛2) , where n is planting density and a, b, and c
are constants as indicated in Table 5.7 in 2011 experiment
117
D-3 Predicted of seeds m-2 plasticity (Pt) as affected by planting
density and soybean varieties were computed by: 𝑃𝑡 =
−[(1 + bn + 2𝑐𝑛2)𝑒(𝑎+bn+𝑐𝑛2)
]) , where n is planting density and
a, b, and c are constants as indicated in Table 5.7 in 2010
experiment
118
D-4 Predicted of seeds m-2 plasticity (Pt) as affected by planting
density and soybean varieties were computed by: 𝑃𝑡 =
−[(1 + bn + 2𝑐𝑛2)𝑒(𝑎+bn+𝑐𝑛2)
]) , where n is planting density and
a, b, and c are constants as indicated in Table 5.7 in 2011
experiment
119
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LIST OF ABBREVIATIONS
CGR Crop growth rate
d Day
DAP Days after planting
DM Dry matter
EFP Effective filling period
ESFP Effective seed filling period
FSS Final seed size
GR Growth rate
H High planting density
L Low planting density
l Leaf
LAI Leaf area index
LDW Leaf dry weight
LGR Leaf growth rate
MMD Malaysia Meteorological Department
N Normal planting density
PDW Plant dry weight
PGR Plant growth rate
pl Plant
pt Plasticity based on per plant basis
Pt Plasticity based on per area basis
s Seed
SDW Seed dry weight
SFP Seed filling period
SGR Seed growth rate
SGRi Individual seed growth rate
RGR Relative growth rate
RGRl Leaf relative growth rate
RGRs Seed relative growth rate
t Time
TDM Total dry matter
TDW Total dry weight
α Allometric coefficient
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CHAPTER 1
GENERAL INTRODUCTION
1 GENERAL INTRODUCTION
Soybean [(Glycine max L.) Merrill.] serves as one of the most valuable crops in the
world, especially among oilseed crops. It accounts for 57% of the total production of
oil seed crops in 2012 and, it is the world's most important grain legume in terms of
the total output and international trade (SoyStats, 2013). It is like a highly nutritive
crop. Its seed contains about 40% protein and 20% oil, and soybean was the source
for 68% and 28% of the global vegetable protein and vegetable oil consumption,
respectively in 2012 (Hymowitz et al., 1998; SoyStats, 2013). Soybeans are grown
in over 35 countries (Rӧbbelen et al., 1998; Weiss, 1983). They are cultivated for
their high protein and oil content, and few varieties with special traits are planted for
vegetable usage (Yinbo et al., 1997). Soybean serves as a valuable plant source for
food, feed, and industrial applications. The industrial uses include soy flour, soy
milk, soy cake, biscuits, enriched cereal flour and other industrial products. Being a
legume plant, it is also enriches the soil by fixing atmospheric nitrogen (Rathore,
2000). Due to their ability to fix nitrogen in the soil, soybean helps to improve
productivity of other food and cash crops particularly in mixed crops, and rotational
farming (Borget, 1992).
There has been an increasing trend in total production of soybean worldwide. The
total production in 1950 was 17.0 million metric tonnes, while in 2011 it was 251.5
million metric tonnes, i.e., with an increase of 14.8 times of that in the 1950’s (Jones,
2003; SoyStats, 2012). This trend seemed to be similar to the pattern of the world
population increase, i.e., the world population in 1950 and 2011 were 2.6 and 7.0
billion, respectively (Population-Statistics, 2014). The major producers of soybean
are Brazil, United States of America, Argentina, China, India, Paraguay, and Canada
where they produce 31%, 31%, 19%, 5%, 4%, 3% and 2%, respectively of the total
world soybeans yield. The respective tonnages are to 83.5, 82.1, 51.5, 12.6,11.5, 7.8,
and 4.9 million metric tonnes (SoyStats, 2013). In East Asia, soybean vegetable
varieties have become quite popular in China, Japan, Korea, and Indonesia (Oerke
and Ecpa, 1994; Shurtleff and Aoyagi, 2009).
High quality seed for planting is a key component of all grain cropping system, and
that in a range of field conditions, high quality seeds are needed in ensuring adequate
plant population with a reasonable seeding rate (Hasan et al., 2013). Seed quality is
the resultant of the integrated effects of the environment during seed production, and
the seed exposure condition during harvest, and storage period (Egli et al., 2005).
The influence of competition among plants in a population is ubiquitous. It is
infrequent to find a plant that has not been affected negatively by its neighbouring
plants (Weiner, 1988). The inter- and intra-specific competition that related to
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density variable among individual plants would cause the reduction in plant growth
and/or increase its probability of death (Selamat, 1987).
In general, crop growth is a function of the internal (genotype) and external
(environment) growth factors (Amiri and Kakolvand, 2014). These factors
ultimately affects yield. Unfavourable growing conditions reduce soybean seed yield
(Frederick et al., 2001). By emphasizing on the yield, the changes could occur in the
amount of reproductive part and/or the timing of the onset of reproductive initiation.
The plant's reproductive photoassimilate allocation might be affected by stresses,
such as high plant densities (high competition), too higher or too low air temperature,
and drought (Lemoine et al., 2013). In a wider sense, biotic and abiotic factors are
affected by plant population density. Therefore, the plant reproductive output are
also affected (Frederick et al., 1998; Linkemer et al., 1998). Optimum plant
population is a major factor in maximizing yield and yield’s profitability. The yield
per unit area increases with the increase in plant population density that generally
follow the pattern of an asymptotic curve of yield versus planting density, i.e.,
smaller increases in total yield are obtained at higher densities but above a certain
density, the yield becomes constant with increasing density (Doust and Doust, 1990).
Sensitivity of soybean to the environmental condition could also be due to the types
of varieties that are grown in specific growing areas. In achieving the maximum
soybean yield potential at those specific areas, some field management should be
determined for the respective varieties, such as optimum plant population density,
planting date, fertilizer requirements, and diseases control practices. Planting and
seedling rates are some of the very important agronomic decisions for farmers to
increase soybean seed yield. Based on the Malaysian weather conditions (rainfall,
temperature, and daylight length), soybean can be planted and produces high yield
with proper management and use of suitable varieties (De Bruin and Pedersen,
2008a; Parsaei, 2011).
Plant densities create different canopy- and root-zone microclimates within plant
population that may affect plant growing behaviour and some of field management
such as harvesting time. In tropical area like Malaysia, planting date is not
constrained by water availability and/or soil temperature, but it may be critical for
harvesting time that due to the momentum effect of density-dependence
microclimate, especially in the reproductive growth stages.
Plants are most affected by stress during pollination, and the dynamic of seed set
during the growth stages in plant development (Alqudah et al., 2011). In order to
determine what influence a plant during its life cycle, one often needs to know more
factor(s) and not than just the end yield or the final dry matter accumulation. Looking
at the yield influencing factors, the plant development as dry matter accumulation at
different reproductive growth stages over time is useful. To agronomists, plant
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growth is frequently defined by the parameters related to the changing time such as
vegetative and reproductive dry matter increases over time. The comparative value
or ratio between the relative growth rates of vegetative and reproductive organs that
is yielding ‘allometry’ could be used in quantifying agronomically and
physiologically the dynamic changes of the respective parts during the growth period
or progress. The vegetative and reproductive changes in plants grown in different
growing environments at certain growth stages could be quantified in term of
plasticity. This plasticity is basically the different performances (based on either per
plant or per population density) of the plants that are grown under two different
growing conditions. Changes occurring along a plant growth trajectory in actual
practice can be interpreted by using the concept of allometry and phenotypic
plasticity. The allometry could indicate the trend of photoassimilate partitioning
from the vegetative to the reproductive parts. However, the proportion of assimilates
that can partitioned to different vegetative and reproductive structures allometrically
are little being studied. Among breeders, varietal improvement is used to increase
crop yield, whereas the plant population density is the main emphasis agronomically
for to be used in seeing the ‘true’ of maximum yield performance of the
recommended variety. One of the approaches is therefore, to carry out research in
identifying the soybean reproductive allocation behaviour that could be determined
by allometrical and plasticity approaches, subjected to plant population density
changes of selected varieties (vegetable- and grain-type soybeans) with respect to
yield improvement. While the information on soybean seed growth and development
is important in achieving higher yield but the reproductive allocation dynamics is
still often confusing, especially for agronomists and plant breeders to produce high
yielding varieties. Thus, this study was conducted with the following objectives:
General Objective:
To evaluate the use of “allometry and plasticity” approaches in comparing several
soybean varieties in relation to changes in plant population densities. The evaluation
takes into consideration the selected physiological and agronomical parameters that
affecting the dynamics of seed growth and development under tropical growing
environment.
Specific Objectives:
1. To determine the effect of plant population density of selected vegetable- and
grain-type varieties of soybean on changes of growth rates and seed fill
duration at specific reproductive growth stages [beginning pod (R3), full pod
(R4), beginning seed (R5), full seed (R6), and beginning physiological
maturity (R7)] and the relationships of individual seed growth rate and seed
filling period to yield components.
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2. To examine the quantitative physiological approaches that are involved in
allometric changes based on relative growth rate of both leaf and seed mass
with source-sink relationship due to plant population pressures of selected
varieties at specific reproductive growth stages.
3. To determine plant density variations on soybean good characteristic of
plasticity resistance in yield in the zone of higher seed number based on
individual plant and per area basis and the use of plasticity for designing the
optimal field planting density.
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